The benefits of moving your on-prem Spark Hadoop environment to Databricks are undeniable. A recent Forrester Total Economic Impact (TEI) study reveals that deploying Databricks can pay for itself in less than six months, with a 417% ROI from cost savings and increased revenue & productivity over three years. But without the right methodology and tools, such modernization/migration can be a daunting task.
Cloud-to-cloud migration can be an expensive, cumbersome, and overwhelming process with no guarantee of success. Yet, moving data from cloud to cloud is becoming more and more common in the public sector as operations are being migrated to the cloud more completely. Factors like complexities in environments, sheer volume of historical data, and application nuances can greatly impact the success or failure of a cloud migration effort.
The cloud is growing more and more popular each day. We are in an era where there is a prominent trend of companies migrating from traditional on-premise systems to more reliable and fast cloud-based systems. However, the conversion is still not rampant on a large scale, primarily due to the lack of awareness in the up-and-coming businesses about the cloud’s fundamentals. However, the cloud has proven to be a sound and worthy option time and time again.
At the DataOps Unleashed 2022 virtual conference, AWS Principal Solutions Architect Angelo Carvalho presented How AWS & Unravel help customers modernize their Big Data workloads with Amazon EMR. The full session recording is available on demand, but here are some of the highlights.
In this series of demystifying the tech trends, my colleagues and I will be looking at busting the buzzwords to help you keep on track. Concerned about puzzling parlance, analytics argot, techie terminology – or plain old jargon? This series breaks down words and concepts to give you the deepest insight and understanding into how to talk the talk in the world of tech, so you can engage in conversations with the confidence of being data literate.
